Analysis and visual presentation of dataset components

ABSTRACT

Methods and systems are disclosed for evaluating and visually displaying the performance of individual components of a portfolio of assets. Information regarding a portfolio may be received and parsed into individual components. The performance of each component may be evaluated by way of performance metrics and compared against corresponding alternative parts. A visual display may be generated that charts the performance of each component against replicability by the corresponding alternative component. Within such a display, each component may be represented by a respective icon, and the size of the icon may correspond to relative size (proportion) of the represented component within the portfolio. Each icon may also have different colors (and saturation thereof) to indicate different information (e.g., degrees of replicability, differences in performance metrics) regarding the represented component.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present patent application is a continuation and claims the prioritybenefit of U.S. patent application Ser. No. 16/360,482 filed Mar. 21,2019, which claims the priority benefit of U.S. patent application62/619,838 filed Jan. 21, 2018, the disclosures of which areincorporated by reference herein.

BACKGROUND OF THE INVENTION 1. Field of the Invention

The invention relates to evaluating the performance of a portfolio'scomponents. More specifically, the invention relates to examiningportfolio component performance, as well as replacing an underperformingportfolio component with a higher performing suggested portfoliocomponent while preserving the essential risk factor profile of theportfolio as a whole.

2. Description of the Related Art

Portfolio managers at financial institutions manage numerous clientportfolios. One of the ways a portfolio manager adds value to aportfolio in service of their clients is by monitoring their portfolios(each comprising a set of components, such as stocks and othersecurities) and evaluating performance on a regular basis. If theportfolio is under-performing, the goal would be to replace all or aportion thereof with alternative components. However, determining whichportion of a portfolio results in under-performance (and to what extent)can be difficult as there may be numerous components, each having adifferent effect. As such, monitoring a portfolio on a regular basis canbe time-consuming and difficult to do consistently. Further, determiningproper metrics to evaluate the value-add in performance of individualcomponents can be challenging.

In addition, even when numerous metrics are available, the problembecomes how to identify which metrics are relevant to and indicative ofperformance and of effect on the whole portfolio. Furthermore, a reportthat expresses such metrics in textual and/or numeric form can beextremely dense and opaque for a person (especially clients) to graspreadily or to easily perform apples-to-apples comparisons across avariety of different metrics.

As such, there is a need in the art for improved systems and methodsthat allow for portfolio analysis on an individual component basis andvisual presentation of the same.

SUMMARY OF THE INVENTION

Embodiments of the present invention may include a computer-implementedmethod for accessing portfolio performance information, evaluating on anindividual basis each portfolio component, filtering for relevance tooverall portfolio performance, swapping out the portfolio component(e.g., with a better-performing portfolio component), or placing thesame on a watch list. Such methods may filter for relevance based onautomatically identifying components of a portfolio to be replaced. Onceidentified, the methods may further including identifying and suggestingalternative components that have the potential to outperform whilepreserving the overall composition and balance of the portfolio.

For each imported portfolio, a visual display of the analytical resultsmay be generated on a graphical user interface. Such visual display mayinclude the extracted and filtered subset of metrics regarding each ofthe imported portfolio components identified as having at least aminimum threshold level of effect on overall portfolio performance. Suchmetrics can be directed at measuring such risk factors as value,momentum, volatility, or other commonly-used factors.

Further embodiments provided that for each portfolio imported, amatching target blend for each portfolio component—based on matching theequivalent factor exposures, a process called premia factor fit(PFF)—may be constructed. Such a target blend may be constructed basedon metrics from the imported portfolio to identify candidate componentsfor replacement. In addition, imported information regarding a targetrisk factor profile may be used to generate a matching PFF portfolio,which may be stored in a database. The component(s) identified ascorresponding to the target PFF portfolio may also be evaluated forperformance, value, and replicability metrics against the correspondingparts of the underperforming portfolio. In one embodiment, the user mayprovide a target threshold or percentage of matching (e.g., as a measureof confidence that is met) for each component suggested for inclusion inthe target PFF portfolio blend as a suitable alternative to thecorresponding component being replaced.

Where multiple portfolio components are being evaluated for eachportfolio, the generated visual display may identify one or moreunderperforming portfolio components. The visual display may furtherinclude suggestions or options (e.g., based on a previously constructedtarget PFF portfolio blend) for making changes so as to more closelymatch the overall composition of the underperforming portfolio whileimproving efficiency of performance by the individual components.

The visual display may therefore provide options for replacing orswapping the underperforming portfolio component with an alternativecomponent corresponding to the target PFF portfolio blend or placing theunderperforming portfolio component on a watch list for subsequentswaps.

In one embodiment, the user (or an automated system using previouslyprovided user input) may replace the underperforming portfolio componentwith the alternative that corresponds to the matching PFF portfolioblend when the matching threshold is met. The replacement may result inselling the underperforming component asset from the current portfolioand purchasing a different component asset corresponding to the targetPFF portfolio blend.

In another embodiment, the different component corresponding to thetarget PFF portfolio blend may be placed on a watch list. In thisinstance, the user may easily identify and track the performance of anunderperforming portfolio compared against its target PFF as reflectedby updated data, and subsequently implement the swap of the componentcorresponding to the target PFF portfolio blend from the database inplace of the underperforming portfolio component.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flow chart illustrating an exemplary method for analyzingthe performance of an existing portfolio against a target portfolioblend according to the disclosed embodiments.

FIG. 2A illustrates an exemplary graphical representation of multipleportfolio components that may be generated according to the disclosedembodiments.

FIG. 2B is a table of data regarding proposed alternative componentscorresponding to a target portfolio blend according to the disclosedembodiments.

FIG. 2C is a diagram illustrating different types of information used toidentify a target portfolio blend.

FIG. 3 is a flowchart illustrating an exemplary method of swapping acomponent of an existing portfolio with an alternative componentcorresponding to the target portfolio blend according to the disclosedembodiments.

FIG. 4 illustrates an exemplary network environment in which a systemfor evaluating portfolio components and generating a visual display maybe implemented according to the disclosed embodiments.

FIG. 5 illustrates an exemplary computing device that may be used toevaluated portfolio components and to generate a visual displayaccording to the disclosed embodiments.

DETAILED DESCRIPTION

FIG. 1 is a flow chart illustrating an exemplary method for analyzingthe performance of an existing portfolio against a target portfolioblend according to the disclosed embodiments.

In step 101, a model (or group of portfolio components) associated witha portfolio may be imported into a user interface (e.g., FactorAllocator Interface) of a computing device. The imported model mayconsist of a variety of assets, such as mutual funds, stocks, and othertypes of publicly and privately traded equity funds and securities.

In step 102, a target portfolio blend may be constructed for theportfolio imported into the Factor Allocator Interface. The targetportfolio, also referred to as the Premia Factor Fit (or PFF), may becreated based on examination of each component of the imported portfolioand mix thereof with respect to a set of predetermined risk factors. Thecreated target PFF portfolio may represent the closest match to theuploaded portfolio in accordance with the set of predetermined riskfactors and may be saved to a database. FIG. 3 provides additionaldetails on how the target PFF portfolio may be constructed, a processwhich may be performed automatically or on-demand. The target portfolioblend may therefore represent a desired composition of risk exposuresthat have been identified for a particular portfolio. Differentcomponents (e.g., stocks and other securities) may be chosen for aportfolio in order to achieve the desired blend. However, a specificcomponent may fit the desired profile, but be underperforming (e.g.,inefficient, associated with additional fees and costs) relative toanother component that also fits the profile. In various embodiments,various available components may be continually updated and refinedbased on updated data to identify how closely such components correspondto different aspects of the target portfolio blend. Such components mayserve as points of comparison and refined to identify a pool ofcandidates for replacing existing components of an analyzed portfolio.

In step 103, the imported portfolio may be decomposed into itscomponents, and the performance of each component may be evaluated basedon a predetermined mix of risk factor metrics. For example, the riskfactor metrics may be based on measuring selected parameters relating tovalue, momentum, quality, and volatility. In other embodiments,different risk factor metrics may be selected and applied via theinterface to the imported portfolio. These risk factor metrics can bedeveloped by the provider of the interface, third parties, or providedby the user (e.g., by way of direct input, upload/download, selectionfrom a menu of options, etc.).

In step 105, the portfolio may be displayed on an X-Y scatter plot thatcharts the performance metrics of each component. Each component may berepresented by an icon in the plot, and the position of each icon alongthe X-axis may be established by an analysis of the respectiveperformance metrics identified in step 103. In the graphical userinterface (also known as The Factor Allocator Interface) illustrated inFIG. 2A, each portfolio component is depicted as a colored circle. Thesize of the circle may represent the size (e.g., monetary amount) of thecomponent within the larger model, and the color may represent thestrength and relative performance of the component within the model. Forexample, a larger circle may be used for a component that has a largermonetary value, and a smaller circle may be used for a relativelysmaller component. Alternatively, other shapes—such as squares,rectangles, etc.—may also be used instead of circles to depict portfoliosize, performance, strength or other characteristics as desired.

In addition, FIG. 2A also illustrates that the color spectrum can rangefrom green to red, where a high-performing component is colored in greenand an underperforming component is colored in red. Other color schemes,shading schemes, and hashing schemes may also be used to show thespectrum from underperforming to high-performing portfolios. The displaymay also include other portfolios from the same or other models that aremanaged by the same portfolio manager.

In step 107, a target portfolio blend may be suggested. As mentionedearlier, the Factor Allocator Interface may examine each portfoliocomponent against Premia Factor Fit (PFF) portfolio blends in terms ofhistorical value-add and correlation to the PFF. Such comparisons (e.g.,of a specific component in the imported portfolio against one or morecorresponding components of the target portfolio blend) may determine ifthe target portfolio blend that represents the PFF may provide asuitable replacement for an underperforming component while maintainingan overall composition that corresponds inter alia to a desired riskfactor profile.

The Factor Allocator Interface may suggest a specific mix of portfoliocomponents identified from the target portfolio blend to replace one ormore components in the existing portfolio. The components of the targetPFF portfolio blend may be identified based on a mix of factors (e.g., x% Value, y % Low Volatility, z % Momentum) and may be adjusteddynamically over time. Components corresponding to the target PFFportfolio blend may be identified based on closely matching thepredetermined factor mix of the current portfolio, and a component fromthe target PFF portfolio blend may be selected to replace acorresponding component based on stronger historical performance. Theinterface may define a match or replicability probability to evaluatehow close of a match the alternative component is to the component beingreplaced. For example, the interface may be set a minimum threshold of80% replicability in order for a component to be considered as acandidate to replace an underperforming component within this frameworkof analysis. Other percentage thresholds can be employed. Furtherdetails of selection of the target PFF portfolio blend is described inrelation to FIG. 2B.

In step 109, one current component may be identified as underperformingand replaced with an alternative component selected from the targetportfolio blend. Such alternative component may have been identified asone that matches most closely in terms of risk factors to the currentcomponent, but with higher historical performance. As such, the overallportfolio may continue to reflect the same predetermined composition ofreference factors, but with higher-performing component(s). Thereplacement may result in several actions being performed, such ascapital from the current portfolio being withdrawn and used to purchasethe identified alternative component in the given proportions, or simplythat the current component and alternative component corresponding tothe target blend may be maintained in a table (or watch list) for futureassessment. Updates on that assessment based on new data can be made andmay be used to trigger subsequent automatic actions (e.g., sale of onecomponent, purchase of an alternative component).

FIG. 2A illustrates an exemplary graphical representation of multipleportfolio components that may be generated according to the disclosedembodiments. As mentioned in relation to FIG. 1, a portfolio'scomponents may be graphically represented on a graphical user interface.The graphical depiction of the portfolio allows a user to quicklydetermine the size, factor replicability, and factor-relativeperformance of the individual components of the portfolio.

The chart of FIG. 2A represents a plurality of portfolio components.Such components may be drawn from one or more selected portfoliosassociated with a portfolio manager, their institution, third parties,or otherwise accessible. Such portfolio(s) may be imported into adatabase via an interface (e.g., Factor Allocator Interface), so as togenerate a visual breakdown of all relevant holdings in terms of apredetermined mix of risk factors.

In the illustrated embodiment, portfolios may be depicted by anicon—such as a circle or other shape—of a certain size. The size of thecircles may represent the proportional size of the component (e.g.,amount or percentage of total amount) within the overall portfolio.

Further, each component in the portfolio may also be color-coded. In theillustrated chart, the color scheme may reflect which components areperforming well (e.g., in relation to historical averages) and whichcomponents are under-performing. In addition, the Factor AllocatorInterface may also places the circle icons along the Y-axis based ontheir replicability (by a corresponding alternative component from thetarget PFF blend) and along the X-axis based on performance (against itscorresponding alternative component from the target PFF blend).

As illustrated, component 201 (depicted as a smaller circle as comparedto component 203) can be visually indicated as proportionally smaller,but having better-performance (against its corresponding alternative)and a higher replicability (by its corresponding alternative) thancomponent 203 (against its respective alternative component). Likewise,component 209, which is represented by a smaller icon than that ofcomponent 201 and 203, is placed in the far-right side of the X-axis(e.g., the performance axis). The icon for component 209 is also coloredred, signifying that it is the worst-performing component compared toother components in the portfolio. Component 207 is illustrated as thelargest circle on the dashboard, signifying a proportionally largerinvestment than other component. Component 207 is also illustrated asred and further to the right along the X-axis, indicating that component207 is underperforming in comparison to alternative component(s)corresponding to a target portfolio blend.

The components to the left of the neutral line 205 are considered to beperforming better than their respective alternative components, and thecomponents to the right side of the neutral line 205 are considered asunderperforming in comparison to their respective alternativecomponents.

FIG. 2B is a table of data regarding proposed alternative componentscorresponding to a target portfolio blend according to the disclosedembodiments. Such a table may serve as a watch list, reflectingcandidates that have been flagged for use in replacing a correspondingcomponent in a current portfolio. As illustrated, the table pertains tothree different components of a portfolio, their comparative performance(against their respective alternative component), replicability, andweight.

The replicability metric—which corresponds to the Y-axis in the chart ofFIG. 2A—indicates how closely the alternative component would replicatethe role (e.g., used to meet different factors and goals) of thecomponent being replaced within the overall composition of theportfolio. A high replicability metric therefore indicates that thealternative component is likely capable of serving very similarfunctions in the composition of the portfolio, while a low replicabilitymetric indicates the alternative component is unlikely to serve the samefunctions. In the chart of FIG. 2A, the portfolio components have beenfiltered such that only components having at least a threshold (e.g.,80%) replicability are included.

Weight—which corresponds to the size of the icons in the chart of FIG.2A—refers to a proportion (e.g., size, monetary amount) represented by acomponent within a portfolio. A more heavily weighted component has moreeffect on the over performance of the portfolio—and replacing the samewould have more significant effect—than a less heavily weightedcomponent.

FIG. 2C is a diagram illustrating different types of information used toidentify a target portfolio blend. As mentioned earlier, a target PFFportfolio may be constructed for each portfolio that is imported intothe Factor Allocator Interface. In one embodiment, a target PFFportfolio may be created within a certain time frame of importing theportfolio. The time frame may vary. For example, the target PFFportfolio may be created automatically in real-time (e.g., instantlybased on a current set of data) or based data gathered over auser-defined time frame. One of the goals of creating a target PFFportfolio is to monitor the performance of the imported portfolioagainst the target PFF portfolio. Yet another goal may be to have atarget PFF portfolio that matches the imported portfolio be readilyavailable in the event one or more components of the imported portfolioneed to be swapped for a corresponding alternative identified from thetarget PFF portfolio. In addition, an institution may also use PFFmetrics to determine whether a portfolio manager's portfolio is meetingor exceeding the PFF returns, i.e. the returns realized by a PFFportfolio.

In operation, the target PFF portfolio may be created by a target PFFgeneration module 251. The portfolio generation module 251 accesses aportfolio database 253, which may include a plurality of differentportfolios (and components) that are within the available universe ofconsideration (e.g., by the institution). The portfolio components maybe evaluated individually or as a blend in the Factor AllocatorInterface. The returns observed by the premia factor portfolios may becalled the Premia Factor Fit (PFF) portfolio. The goal of a PFF is toact as a custom factor benchmark that is specific to each portfoliocomponent. The portfolio generation module 251 may also access otherexternal portfolios 255 that are outside the institution or the databaseand constructed by third parties (e.g., available for search andretrieval using the Internet). The portfolio generation module 251examines the target portfolio blend that is obtained either from theportfolio database 253 or an external portfolio 255 against a pluralityof criterion.

For example, the portfolio generation module 251 may examine the targetportfolio blend against historical performance 257, value 259, andreplicability 261. Other criteria may also be established by the user orautomatically generated for examination.

Once the portfolio generation module 251 examines the imported portfoliobased on the predetermined criteria (e.g., the above-mentioned criteria,user-defined criteria, or automated criteria), a systematic rebalancingrule may be applied on the closest-mix factor weights, and theunderlying portfolios that represent the blend may therefore change ateach rebalance period.

FIG. 3 is a flowchart illustrating an exemplary method of swapping acomponent of an existing portfolio with an alternative componentcorresponding to the target portfolio blend according to the disclosedembodiments.

In step 301, an underperforming portfolio is selected. Theunderperforming portfolio may be one of many portfolios managed by aninstitution or a portfolio manager or part of a database of portfolios.The user may have defined a threshold (e.g., underperformance by 2%) toselect the current portfolio for adjustment. The components of theselected portfolio may be individually analyzed to identify a set of atleast one underperforming component (in comparison to correspondingalternative components having similar composition profiles).

Once selected, the underperforming component is analyzed to extract allrelevant metrics required to understand its composition and risk premia.For example, the component may be analyzed to determine the factor blendfor the portfolio, including value, quality, momentum, and volatilityexposure, and other risk premia factors. The goal for extracting thesemetrics is for use in finding a comparable portfolio with similarmetrics that has performed better than the existing portfolio, therebyindicating the potential to do so in the future as well (the PFF).

In step 303, a matching PFF portfolio blend that approximates eachcurrent portfolio component is presented. As mentioned earlier anddescribed in FIG. 1, a target PFF portfolio blend may be created aroundthe time the portfolio was imported. As such, a target PFF portfolioblend that has been previously created, and an alternative componenttherefrom may be previously determined to be a suitable replacement(e.g., meeting replicability threshold) for the specific underperformingcomponent may be made readily available for comparison, visualpresentation, and (upon approval) replacement.

In step 303, the target PFF portfolio blend is presented. At this point,the user has the option to either go to step 307 to replace theunderperforming component with the identified alternative component.Alternatively, the user may elect to proceed to step 309, where thealternative component is added to a watch list in a database. In someembodiments, the user may further specify triggers whereby theunderperforming component is automatically replaced when certainconditions (e.g., timing, performance) are met.

If a swap is made, such a swap may include selling of theunderperforming component in the current portfolio and buying thealternative component corresponding to the target PFF portfolio blend.The swap may also result in other actions, such as obtaining funds,transferring funds form a bank, and purchasing an additional componentwithout a corresponding sale of an underperforming component.Alternatively, the underperforming component, as well as the respectivetarget PFF portfolio blend, can be maintained on a “watch list” forfurther evaluation.

FIG. 4 illustrates an exemplary network environment in which a systemfor evaluating portfolio component parts and generating a visual displaymay be implemented according to the disclosed embodiments. Othercomponents may be included in system 400 not shown in FIG. 4. System 400may include local area networks (LAN) and wide area network (WAN) shownas network and wireless network. Client computing devices may includeany device capable of receiving and sending data over a network, such aswireless network. Devices may include portable devices such as cellulartelephones, smart phones, radio frequency-enabled devices, personaldigital assistants, handheld computers, tablets, laptop computers,wearable computers and the like. Devices also may include any computingdevice that connects to a network using a wired communications mediumsuch as personal computers, multiprocessor systems, microprocessor-basedor programmable consumer electronics, network personal computers and thelike.

Client computing devices also may include at least one other clientapplication that is configured to receive content from another computingdevice, including, without limit, server computing devices. Server alsocomprises server app and database.

Network is configured to couple one or more servers computing devicesand their respective components with other computing devices, such asclient device, and through wireless network to client devices.

FIG. 5 illustrates an exemplary computing device that may be used toevaluated portfolio components and to generate a visual displayaccording to the disclosed embodiments. Computing device 500communicates with other devices over system 400 to perform the functionsneeded for generating, managing, and replacing one or more portfolios.Computing device 500 includes optical storage, central processing unit(CPU), memory module, display interface, input devices, input/output(I/O) processor, bus, non-volatile memory, network interface card (NIC),hard disk, power supply, and a transceiver. Computing device 500 isconfigured to be a special purpose device for generating, managing, andreplacing a plurality of portfolio and performing disclosed steps infigures above.

The present invention may be implemented in an application that may beoperable using a variety of devices. Non-transitory computer-readablestorage media refer to any medium or media that participate in providinginstructions to a central processing unit (CPU) for execution. Suchmedia can take many forms, including, but not limited to, non-volatileand volatile media such as optical or magnetic disks and dynamic memory,respectively. Common forms of non-transitory computer-readable mediainclude, for example, a floppy disk, a flexible disk, a hard disk,magnetic tape, any other magnetic medium, a CD-ROM disk, digital videodisk (DVD), any other optical medium, RAM, PROM, EPROM, a FLASHEPROM,and any other memory chip or cartridge.

Various forms of transmission media may be involved in carrying one ormore sequences of one or more instructions to a CPU for execution. A buscarries the data to system RAM, from which a CPU retrieves and executesthe instructions. The instructions received by system RAM can optionallybe stored on a fixed disk either before or after execution by a CPU.Various forms of storage may likewise be implemented as well as thenecessary network interfaces and network topologies to implement thesame.

The foregoing detailed description of the technology has been presentedfor purposes of illustration and description. It is not intended to beexhaustive or to limit the technology to the precise form disclosed.Many modifications and variations are possible in light of the aboveteaching. The described embodiments were chosen in order to best explainthe principles of the technology, its practical application, and toenable others skilled in the art to utilize the technology in variousembodiments and with various modifications as are suited to theparticular use contemplated. It is intended that the scope of thetechnology be defined by the claim.

What is claimed is:
 1. A method for visually displaying comparisons ofdataset components, the method comprising: receiving importedinformation via a communication interface regarding a dataset;identifying a composition of the dataset, wherein the identifiedcomposition includes a plurality of components each in a specifiedproportion within the dataset, each identified component associated withat least one alternative component having an identified similarity tothe respective identified component as measured by a replicabilitymetric; filtering the identified components based on a replicabilitymetric threshold, wherein one or more of the components are excludedfrom further analysis based on the filtering; and generating a visualdisplay that charts the filtered components within a graphical userinterface of a display screen, the visual display including an iconcorresponding to each of the filtered components, wherein a size of theicon corresponds to the specified proportion of the respective filteredcomponent within the dataset.
 2. The method of claim 1, wherein alocation of the icon corresponding to the respective filtered componentwithin the visual display is based on the replicability metric.
 3. Themethod of claim 1, wherein a location of the icon corresponding to therespective filtered component within the visual display is based on ahistoric metric characterizing a comparison between the respectivefiltered component and at least one alternative component.
 4. The methodof claim 1, wherein a color of the icon is selected from a predeterminedcolor spectrum across a range of one or more colors based on a locationof the icon.
 5. The method of claim 1, further comprising identifyingthe at least one alternative component in real-time, and monitoring thedataset of the plurality of components in comparison to the at least onealternative component.
 6. The method of claim 5, wherein identifying theat least one alternative component in real-time includes searching oneor more databases accessible over a communication network based on eachof the identified components.
 7. The method of claim 1, furthercomprising flagging one or more alternative components in the visualdisplay as candidates for replacing a corresponding filtered component.8. The method of claim 1, further comprising receiving input specifyingaddition of one of the filtered components charted in the visual displayto a watch list.
 9. The method of claim 8, wherein the input furtherspecifies one or more conditions for triggering replacement of thefiltered component on the watch list with a corresponding alternativecomponent, and further comprising automatically initiating thereplacement when the specified conditions are identified as having beenmet.
 10. A system for visually displaying comparisons of datasetcomponents, the system comprising: a communication interface thatreceives imported information regarding a dataset; and a processor thatexecutes instructions stored in memory, wherein the processor executesthe instructions to: identify a composition of the dataset, wherein theidentified composition includes a plurality of components each in aspecified proportion within the dataset, each identified componentassociated with at least one alternative component having an identifiedsimilarity to the respective identified component as measured by areplicability metric; filter the identified components based on areplicability metric threshold, wherein one or more of the componentsare excluded from further analysis based on the filtering; and generatea visual display that charts the filtered components within a graphicaluser interface of a display screen, the visual display including an iconcorresponding to each of the filtered components, wherein a size of theicon corresponds to the specified proportion of the respective filteredcomponent within the dataset.
 11. The system of claim 10, wherein alocation of the icon corresponding to the respective filtered componentwithin the visual display is based on the replicability metric.
 12. Thesystem of claim 10, wherein a location of the icon corresponding to therespective filtered component within the visual display is based on ahistoric metric characterizing a comparison between the respectivefiltered component and at least one alternative component.
 13. Thesystem of claim 10, wherein a color of the icon is selected from apredetermined color spectrum across a range of one or more colors basedon a location of the icon.
 14. The system of claim 10, wherein theprocessor executes further instructions to identify the at least onealternative component in real-time, and to monitor the dataset of theplurality of components in comparison to the at least one alternativecomponent.
 15. The system of claim 14, wherein the processor identifiesthe at least one alternative component in real-time by searching one ormore databases accessible over a communication network based on each ofthe identified components.
 16. The system of claim 10, wherein theprocessor executes further instructions to flag one or more alternativecomponents in the visual display as candidates for replacing acorresponding filtered component.
 17. The system of claim 10, whereinthe communication interface further receives input specifying additionof one of the filtered components charted in the visual display to awatch list.
 18. The system of claim 17, wherein the input furtherspecifies one or more conditions for triggering replacement of thefiltered component on the watch list with a corresponding alternativecomponent, and wherein the processor executes further instructions toautomatically initiate the replacement when the specified conditions areidentified as having been met.
 19. A non-transitory, computer-readablestorage medium having embodied thereon a program executable by aprocessor to perform method for visually displaying comparisons ofdataset components, the method comprising: receiving importedinformation via a communication interface regarding a dataset;identifying a composition of the dataset, wherein the identifiedcomposition includes a plurality of components each in a specifiedproportion within the dataset, each identified component associated withat least one alternative component having an identified similarity tothe respective identified component as measured by a replicabilitymetric; filtering the identified components based on a replicabilitymetric threshold, wherein one or more of the components are excludedfrom further analysis based on the filtering; and generating a visualdisplay that charts the filtered components within a graphical userinterface of a display screen, the visual display including an iconcorresponding to each of the filtered components, wherein a size of theicon corresponds to the specified proportion of the respective filteredcomponent within the dataset.